Senior Data Engineer - BigData Development

Project description

We are looking for an experienced Senior Data Engineer to join a project within observability and embedded analytics for a leading automotive Client. The project focuses on transforming logs, events, measurements and telemetry from embedded, cloud, test and application systems into trusted and reusable datasets and engineering insights. You will have a hands-on role in building production data pipelines, transformations and analysis-ready datasets that support faster troubleshooting, reliability analysis, product-quality follow-up and improved understanding of platform performance in real-world conditions.

Responsibilities

• - Design, build and maintain production-grade data pipelines and transformations. - Develop data models, schemas and curated datasets for different engineering use cases. - Process logs, events, telemetry and high-volume time-series data. - Integrate data from embedded, cloud, test and application sources using APIs and other data interfaces. - Implement automated data-quality checks and pipeline monitoring. - Build analysis-ready datasets supporting troubleshooting, reliability and product-quality analysis. - Improve pipeline reliability, performance and maintainability. - Support dashboards and analytical use cases. - Document delivered solutions and support knowledge transfer.

SKILLS

Must have

• - Strong experience developing and operating production-grade data pipelines. - Strong hands-on Python and SQL skills. - Strong knowledge of data transformation and data modelling. - Experience with cloud-based data solutions. - Experience with data orchestration and automated workflows. - Experience working with APIs, event data and logs. - Experience with data quality and pipeline monitoring. - Experience working with high-volume time-series and/or telemetry data.

Nice to have

- Automotive or connected-car experience. - Experience working with data from embedded systems or devices. - Experience supporting troubleshooting, reliability or product-quality analytics. - Experience with data visualisation and dashboards. - Mobile analytics experience. - Knowledge of data lineage and data governance.